{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:DDFYDJBIWAAQJWQBUPDJ7A45N7","short_pith_number":"pith:DDFYDJBI","canonical_record":{"source":{"id":"2605.23775","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-22T15:43:16Z","cross_cats_sorted":[],"title_canon_sha256":"35a2f68003b3b49f224da37c0ce737f4e86324e5a8582612d8c84ac7e7b36cb1","abstract_canon_sha256":"5613ab32f20fb3361b1cb021bc1b20afb0614adc11f93b3011cdd222ffb69fd3"},"schema_version":"1.0"},"canonical_sha256":"18cb81a428b00104da01a3c69f839d6fc5a41813fc0d00948973b8e5779cd4ba","source":{"kind":"arxiv","id":"2605.23775","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.23775","created_at":"2026-05-25T02:02:31Z"},{"alias_kind":"arxiv_version","alias_value":"2605.23775v1","created_at":"2026-05-25T02:02:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.23775","created_at":"2026-05-25T02:02:31Z"},{"alias_kind":"pith_short_12","alias_value":"DDFYDJBIWAAQ","created_at":"2026-05-25T02:02:31Z"},{"alias_kind":"pith_short_16","alias_value":"DDFYDJBIWAAQJWQB","created_at":"2026-05-25T02:02:31Z"},{"alias_kind":"pith_short_8","alias_value":"DDFYDJBI","created_at":"2026-05-25T02:02:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:DDFYDJBIWAAQJWQBUPDJ7A45N7","target":"record","payload":{"canonical_record":{"source":{"id":"2605.23775","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-22T15:43:16Z","cross_cats_sorted":[],"title_canon_sha256":"35a2f68003b3b49f224da37c0ce737f4e86324e5a8582612d8c84ac7e7b36cb1","abstract_canon_sha256":"5613ab32f20fb3361b1cb021bc1b20afb0614adc11f93b3011cdd222ffb69fd3"},"schema_version":"1.0"},"canonical_sha256":"18cb81a428b00104da01a3c69f839d6fc5a41813fc0d00948973b8e5779cd4ba","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-25T02:02:31.931875Z","signature_b64":"NjxypkHLuQGHy20is2k6+RNoq/BERdri8rAALhP5MreQkfn/TmdRW1TFgT2oUanYBQ1B7wd4AEwHkU4ZaF5HDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"18cb81a428b00104da01a3c69f839d6fc5a41813fc0d00948973b8e5779cd4ba","last_reissued_at":"2026-05-25T02:02:31.931138Z","signature_status":"signed_v1","first_computed_at":"2026-05-25T02:02:31.931138Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.23775","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-25T02:02:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Nk8Qef5uPuWApSsDmEmAJxLgb5Cdx8/Hj0puR9EVo+XCi82NPUj3Pfk61wqa72fBr2QCB8/ydo27Dw0flFY/CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T15:51:40.152797Z"},"content_sha256":"96176be9274e999ef65145bd3d9cc2cfc960acae6cf2d6637feacb4213d12b78","schema_version":"1.0","event_id":"sha256:96176be9274e999ef65145bd3d9cc2cfc960acae6cf2d6637feacb4213d12b78"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:DDFYDJBIWAAQJWQBUPDJ7A45N7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Novel Approach for the Counting of Wood Logs Using cGANs and Image Processing Techniques","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Elioenai MF Diniz, \\'Erick O Rodrigues, Gilson A Oliveira, Giovani Bernardes Vitor, Gustavo Tiecker, Jo\\~ao VC Mazzochin, Marcelo Trentin","submitted_at":"2026-05-22T15:43:16Z","abstract_excerpt":"This study tackles the challenge of precise wood log counting, where applications of the proposed methodology can span from automated approaches for materials management, surveillance, and safety science to wood traffic monitoring, wood volume estimation, and others. We introduce an approach leveraging Conditional Generative Adversarial Networks (cGANs) for eucalyptus log segmentation in images, incorporating specialized image processing techniques to handle noise and intersections, coupled with the Connected Components Algorithm for efficient counting. To support this research, we created and"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.23775","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.23775/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-25T02:02:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GPyeE809HYip9RAzjLn0bk0rA3/qEkhOul3fBpRJxMCFdpZ59gcGHndgLqE4ujomgeqKvkAuw6ooaKIFPMYUAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T15:51:40.153616Z"},"content_sha256":"655a0f1ca78c225a762f87cdbfcd84d598e3f64c00febde07cc2b3f6e85ea036","schema_version":"1.0","event_id":"sha256:655a0f1ca78c225a762f87cdbfcd84d598e3f64c00febde07cc2b3f6e85ea036"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DDFYDJBIWAAQJWQBUPDJ7A45N7/bundle.json","state_url":"https://pith.science/pith/DDFYDJBIWAAQJWQBUPDJ7A45N7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DDFYDJBIWAAQJWQBUPDJ7A45N7/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-09T15:51:40Z","links":{"resolver":"https://pith.science/pith/DDFYDJBIWAAQJWQBUPDJ7A45N7","bundle":"https://pith.science/pith/DDFYDJBIWAAQJWQBUPDJ7A45N7/bundle.json","state":"https://pith.science/pith/DDFYDJBIWAAQJWQBUPDJ7A45N7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DDFYDJBIWAAQJWQBUPDJ7A45N7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:DDFYDJBIWAAQJWQBUPDJ7A45N7","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"5613ab32f20fb3361b1cb021bc1b20afb0614adc11f93b3011cdd222ffb69fd3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-22T15:43:16Z","title_canon_sha256":"35a2f68003b3b49f224da37c0ce737f4e86324e5a8582612d8c84ac7e7b36cb1"},"schema_version":"1.0","source":{"id":"2605.23775","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.23775","created_at":"2026-05-25T02:02:31Z"},{"alias_kind":"arxiv_version","alias_value":"2605.23775v1","created_at":"2026-05-25T02:02:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.23775","created_at":"2026-05-25T02:02:31Z"},{"alias_kind":"pith_short_12","alias_value":"DDFYDJBIWAAQ","created_at":"2026-05-25T02:02:31Z"},{"alias_kind":"pith_short_16","alias_value":"DDFYDJBIWAAQJWQB","created_at":"2026-05-25T02:02:31Z"},{"alias_kind":"pith_short_8","alias_value":"DDFYDJBI","created_at":"2026-05-25T02:02:31Z"}],"graph_snapshots":[{"event_id":"sha256:655a0f1ca78c225a762f87cdbfcd84d598e3f64c00febde07cc2b3f6e85ea036","target":"graph","created_at":"2026-05-25T02:02:31Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2605.23775/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study tackles the challenge of precise wood log counting, where applications of the proposed methodology can span from automated approaches for materials management, surveillance, and safety science to wood traffic monitoring, wood volume estimation, and others. We introduce an approach leveraging Conditional Generative Adversarial Networks (cGANs) for eucalyptus log segmentation in images, incorporating specialized image processing techniques to handle noise and intersections, coupled with the Connected Components Algorithm for efficient counting. To support this research, we created and","authors_text":"Elioenai MF Diniz, \\'Erick O Rodrigues, Gilson A Oliveira, Giovani Bernardes Vitor, Gustavo Tiecker, Jo\\~ao VC Mazzochin, Marcelo Trentin","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-22T15:43:16Z","title":"A Novel Approach for the Counting of Wood Logs Using cGANs and Image Processing Techniques"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.23775","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:96176be9274e999ef65145bd3d9cc2cfc960acae6cf2d6637feacb4213d12b78","target":"record","created_at":"2026-05-25T02:02:31Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"5613ab32f20fb3361b1cb021bc1b20afb0614adc11f93b3011cdd222ffb69fd3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-22T15:43:16Z","title_canon_sha256":"35a2f68003b3b49f224da37c0ce737f4e86324e5a8582612d8c84ac7e7b36cb1"},"schema_version":"1.0","source":{"id":"2605.23775","kind":"arxiv","version":1}},"canonical_sha256":"18cb81a428b00104da01a3c69f839d6fc5a41813fc0d00948973b8e5779cd4ba","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"18cb81a428b00104da01a3c69f839d6fc5a41813fc0d00948973b8e5779cd4ba","first_computed_at":"2026-05-25T02:02:31.931138Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-25T02:02:31.931138Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NjxypkHLuQGHy20is2k6+RNoq/BERdri8rAALhP5MreQkfn/TmdRW1TFgT2oUanYBQ1B7wd4AEwHkU4ZaF5HDw==","signature_status":"signed_v1","signed_at":"2026-05-25T02:02:31.931875Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.23775","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:96176be9274e999ef65145bd3d9cc2cfc960acae6cf2d6637feacb4213d12b78","sha256:655a0f1ca78c225a762f87cdbfcd84d598e3f64c00febde07cc2b3f6e85ea036"],"state_sha256":"40899b4ade7226f290825d6be4c84df16119ce893608bf27ed6b7a43c26d4f82"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/ta+uAjB6w2N2HSxQnEgD7jUPM/LR9NFJeIn4+38HDNh/Sdx1HwPzStGTz0v3WwO7PhBQVvdPnyUnO55Qsh2Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T15:51:40.158204Z","bundle_sha256":"932db41894841675467abdab040f09f802d2d6512b5ca0b3adfed8909f6b847c"}}